Trace element profiling using inductively coupled plasma mass spectrometry and its application in an osteoarthritis study

Abstract

In this study, a novel method of quantitatively measuring serum trace elements using inductively coupled plasma mass spectrometry (ICP-MS) coupled with multivariate statistical analysis was developed and applied successfully to the study of osteoarthritis (OA). This technology provides potential advantages over conventional targeted elemental analysis in that it achieves high throughput measurement, small sample volume, and simple operational procedure. Such an unbiased method is particularly suitable for large scale discovery research on trace element based biomarkers. The method optimization and validation study involved accuracy and perturbation testing which focused on estimating the ability of the method to resist interferences in ICP-MS analysis, particularly those of mass <82 amu, in the serum sample. The developed method was successfully applied to the study of serum samples from OA patients. As a result, the serum trace element profiles of OA patients were distinctively separated from those of the healthy controls (HC) using an Orthogonal Projections to Latent Structures Discriminant Analysis (OPLSDA) model. Additionally, significantly differential elements correlated with OA, such as Li and Sn, were identified as potential elemental-based biomarkers.

title = "Trace element profiling using inductively coupled plasma mass spectrometry and its application in an osteoarthritis study",

abstract = "In this study, a novel method of quantitatively measuring serum trace elements using inductively coupled plasma mass spectrometry (ICP-MS) coupled with multivariate statistical analysis was developed and applied successfully to the study of osteoarthritis (OA). This technology provides potential advantages over conventional targeted elemental analysis in that it achieves high throughput measurement, small sample volume, and simple operational procedure. Such an unbiased method is particularly suitable for large scale discovery research on trace element based biomarkers. The method optimization and validation study involved accuracy and perturbation testing which focused on estimating the ability of the method to resist interferences in ICP-MS analysis, particularly those of mass <82 amu, in the serum sample. The developed method was successfully applied to the study of serum samples from OA patients. As a result, the serum trace element profiles of OA patients were distinctively separated from those of the healthy controls (HC) using an Orthogonal Projections to Latent Structures Discriminant Analysis (OPLSDA) model. Additionally, significantly differential elements correlated with OA, such as Li and Sn, were identified as potential elemental-based biomarkers.",

N2 - In this study, a novel method of quantitatively measuring serum trace elements using inductively coupled plasma mass spectrometry (ICP-MS) coupled with multivariate statistical analysis was developed and applied successfully to the study of osteoarthritis (OA). This technology provides potential advantages over conventional targeted elemental analysis in that it achieves high throughput measurement, small sample volume, and simple operational procedure. Such an unbiased method is particularly suitable for large scale discovery research on trace element based biomarkers. The method optimization and validation study involved accuracy and perturbation testing which focused on estimating the ability of the method to resist interferences in ICP-MS analysis, particularly those of mass <82 amu, in the serum sample. The developed method was successfully applied to the study of serum samples from OA patients. As a result, the serum trace element profiles of OA patients were distinctively separated from those of the healthy controls (HC) using an Orthogonal Projections to Latent Structures Discriminant Analysis (OPLSDA) model. Additionally, significantly differential elements correlated with OA, such as Li and Sn, were identified as potential elemental-based biomarkers.

AB - In this study, a novel method of quantitatively measuring serum trace elements using inductively coupled plasma mass spectrometry (ICP-MS) coupled with multivariate statistical analysis was developed and applied successfully to the study of osteoarthritis (OA). This technology provides potential advantages over conventional targeted elemental analysis in that it achieves high throughput measurement, small sample volume, and simple operational procedure. Such an unbiased method is particularly suitable for large scale discovery research on trace element based biomarkers. The method optimization and validation study involved accuracy and perturbation testing which focused on estimating the ability of the method to resist interferences in ICP-MS analysis, particularly those of mass <82 amu, in the serum sample. The developed method was successfully applied to the study of serum samples from OA patients. As a result, the serum trace element profiles of OA patients were distinctively separated from those of the healthy controls (HC) using an Orthogonal Projections to Latent Structures Discriminant Analysis (OPLSDA) model. Additionally, significantly differential elements correlated with OA, such as Li and Sn, were identified as potential elemental-based biomarkers.